The course gives a comprehensive introduction to machine learning, which is a field concerned with learning from examples and has roots in computer science, statistics and pattern recognition. The objective is realized by presenting methods and tools proven valuable and by addressing specific application problems.
The program is based on a combination of academic, problem-oriented and interdisciplinary approaches and organized based on the following work and evaluation methods that combine skills and reflection:
Since it is a 5 ECTS course module, the work load is expected to be 150 hours for the student
|Name of exam
|Type of exam
Written or oral exam
|Type of grading
|Criteria of assessment
|The criteria of assessment are stated in the Examination Policies and Procedures
On this semester two courses must be chosen out of three elective courses (total: 10 ECTS).
|Language of instruction
|Location of the lecture
|Responsible for the module
|Study Board of Build, Energy, Electronics and Mechanics in Esbjerg
|Department of Energy
|The Faculty of Engineering and Science